Effects of systematic errors in blood pressure measurements on the diagnosis of hypertension
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To estimate the effects of systematic errors in measurements of blood pressure on the diagnosis of hypertension. METHODS: We fitted regression curves to distributions of diastolic and systolic BP from recent Canadian and UK surveys and calculated the effect of systematic measurement errors on changes in the numbers of patients who would be classified hypertensive at thresholds of 85, 90 and 95 mmHg diastolic and 140 and 160 mmHg systolic pressure respectively. RESULTS: Overestimation of diastolic BP by 5 mmHg increases the number of patients whose diastolic BP exceeds 85, 90 and 95 mmHg by 102, 132 and 166% respectively. Equivalent underestimation causes 57, 62 and 67% respectively of hypertensive patients to be missed. If systematic error in diastolic pressure is limited to +/-1 mmHg the diagnosis errors are between -15 and +23%. Overestimation of systolic BP by 3 and 5 mmHg increases the number classified as hypertensive by 24 and 43% respectively. Equivalent underestimation causes 19 and 30% of patients with systolic hypertension to be missed. CONCLUSIONS: Small systematic errors in BP measurements may cause large variations in the proportion of patients diagnosed as hypertensive. To limit over- or under-diagnosis of diastolic hypertension to approximately 20%, systematic errors in diastolic BP measurements should be limited to 1 mmHg. An uncertainty of 3 mmHg may be adequate for detecting systolic hypertension.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it